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DBMS > Apache Impala vs. Informix vs. Microsoft Azure Data Explorer vs. Quasardb

System Properties Comparison Apache Impala vs. Informix vs. Microsoft Azure Data Explorer vs. Quasardb

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonInformix  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataFully managed big data interactive analytics platformDistributed, high-performance timeseries database
Primary database modelRelational DBMSRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websiteimpala.apache.orgwww.ibm.com/­products/­informixazure.microsoft.com/­services/­data-explorerquasar.ai
Technical documentationimpala.apache.org/­impala-docs.htmlinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
docs.microsoft.com/­en-us/­azure/­data-explorerdoc.quasar.ai/­master
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Microsoftquasardb
Initial release2013198420192009
Current release4.1.0, June 202214.10.FC5, November 2020cloud service with continuous releases3.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree developer edition availablecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++ and JavaC++
Server operating systemsLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedBSD
Linux
OS X
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyes infoSince Version 12.10 support for JSON/BSON datatypesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infointeger and binary
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesno
Secondary indexesyesyesall fields are automatically indexedyes infowith tags
SQL infoSupport of SQLSQL-like DML and DDL statementsyesKusto Query Language (KQL), SQL subsetSQL-like query language
APIs and other access methodsJDBC
ODBC
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesYes, possible languages: KQL, Python, Rno
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infoTransient mode
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authentication, authorization, and auditing controlsAzure Active Directory AuthenticationCryptographically strong user authentication and audit trail

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More resources
Apache ImpalaInformixMicrosoft Azure Data ExplorerQuasardb
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